Positioning method and communication device

Abstract

A positioning method and a communication device, and pertains to the field of wireless communication technologies. The positioning method of embodiments of this application includes: receiving, by a first communication device, first positioning request information; and determining and/or sending, by the first communication device, an artificial intelligence network model and/or artificial intelligence network model parameter in response to the first positioning request information, where the artificial intelligence network model is used for obtaining or optimizing positioning signal measurement information of a target terminal and/or location information of a target terminal.

What is claimed is: 
     
         1 . A positioning method, comprising:
 receiving, by a first communication device, first positioning request information; and   determining and/or sending, by the first communication device, a target artificial intelligence network model and/or target artificial intelligence network model parameter in response to the first positioning request information, wherein the target artificial intelligence network model is used for obtaining or optimizing positioning signal measurement information of a target terminal and/or location information of a target terminal.   
     
     
         2 . The positioning method according to  claim 1 , wherein the first positioning request information comprises at least one of the following:
 first measurement information;   identity document (ID) of artificial intelligence network model and/or artificial intelligence network model parameter;   artificial intelligence network model;   some or all of artificial intelligence network model parameters;   complexity information of artificial intelligence network model;   type information of artificial intelligence network model;   first parameter information, wherein the first parameter information is used for determining input information and/or output information of artificial intelligence network model, used for determining network structure and/or parameter information of artificial intelligence network model, or used for determining positioning information reported or fed back; or   first indication information, used to indicate whether to request an artificial intelligence network model and/or artificial intelligence network model parameter.   
     
     
         3 . The positioning method according to  claim 2 , wherein the first measurement information comprises at least one of the following:
 positioning signal measurement information of the target terminal;   location information of the target terminal; or   error information, wherein the error information comprises at least one of the following: location error value, measurement error value, artificial intelligence network model error value or parameter error value.   
     
     
         4 . The positioning method according to  claim 3 , wherein the positioning signal measurement information of the target terminal comprises at least one of the following:
 channel response information of positioning signal;   reference signal time difference (RSTD) measurement result;   round-trip time (RTT);   angle of arrival (AOA) measurement result;   angle of departure (AOD) measurement result; or   reference signal received power (RSRP); or   wherein the positioning signal measurement information is associated with or comprises at least one piece of line of sight (LOS) indication information, or comprises positioning signal measurement information of at least one path.   
     
     
         5 . The positioning method according to  claim 2 , wherein the artificial intelligence network model parameter comprises at least one of the following:
 structure of artificial intelligence network model;   multiplicative coefficient, additive coefficient and/or activation function of each neuron of artificial intelligence network model;   complexity information of artificial intelligence network model;   expected training count of artificial intelligence network model;   application document of artificial intelligence network model;   input format of artificial intelligence network model; or   output format of artificial intelligence network model.   
     
     
         6 . The positioning method according to  claim 2 , wherein the type information of artificial intelligence network model comprises at least one of the following:
 fully connected model;   first type, wherein the first type is terminal location information obtained by the first communication device based on the artificial intelligence network model;   second type, wherein the second type is terminal positioning signal measurement information obtained by the first communication device based on the artificial intelligence network model;   third type, wherein the third type is terminal positioning signal measurement information obtained by the first communication device under assistance of a second communication device based on the artificial intelligence network model;   fourth type, wherein the fourth type is terminal location information obtained by the first communication device under assistance of the second communication device based on the artificial intelligence network model;   fifth type, wherein the fifth type is terminal location information obtained by the second communication device under instruction of the first communication device based on the artificial intelligence network model;   sixth type, wherein the sixth type is terminal positioning signal measurement information obtained by the second communication device under instruction of the first communication device based on the artificial intelligence network model;   seventh type, wherein the seventh type is one of terminal positioning signal measurement information and terminal location information obtained by the first communication device based on the artificial intelligence network model, or the other of the terminal positioning signal measurement information or terminal location information obtained by the second communication device based on the artificial intelligence network model; or   unsupervised model or supervised model.   
     
     
         7 . The positioning method according to  claim 1 , before the determining and/or sending, by the first communication device, a target artificial intelligence network model and/or target artificial intelligence network model parameter in response to the first positioning request information, further comprising:
 sending or receiving, by the first communication device, pre-configured information, wherein the pre-configured information comprises at least one of the following:   one or more pre-configured artificial intelligence network models; and   one or more sets of pre-configured artificial intelligence network model parameters.   
     
     
         8 . The positioning method according to  claim 1 , wherein the determining and/or sending, by the first communication device, a target artificial intelligence network model and/or target artificial intelligence network model parameter in response to the first positioning request information further comprises:
 sending, by the first communication device, at least two target artificial intelligence network models and/or target artificial intelligence network model parameters in response to the first positioning request information.   
     
     
         9 . The positioning method according to  claim 2 , wherein the first positioning request information further comprises:
 LOS confidence coefficient; and   second information.   
     
     
         10 . The positioning method according to  claim 2 , wherein the first parameter information comprises at least one of the following:
 length of channel impulse response (CIR);   number of paths in multipath;   bandwidth of CIR;   frequency domain information of signal;   time information;   phase information;   angle information;   energy information;   CIR information processed based on third artificial intelligence model or third artificial intelligence model parameter; or   multipath information processed based on third artificial intelligence model or third artificial intelligence model parameter.   
     
     
         11 . The positioning method according to  claim 2 , further comprising:
 sending, by the first communication device, second parameter information, wherein the second parameter information comprises at least one of the following:   CIR;   multipath measurement result of first positioning reference signal;   time information;   phase information;   angle information;   energy information;   second indication information, wherein the second indication information is used to indicate whether to obtain or optimize other second parameter information through a fourth artificial intelligence network model structure or fourth artificial intelligence network model parameter, or whether to obtain or optimize the positioning signal measurement information of the target terminal and/or location information of the target terminal through the target artificial intelligence network model;   fourth artificial intelligence network model structure; or   fourth artificial intelligence network model parameter; and   wherein the second parameter information is determined based on the first parameter information.   
     
     
         12 . The positioning method according to  claim 1 , further comprising:
 reporting, by the first communication device, capability information, wherein the capability information comprises at least one of the following:   whether the artificial intelligence network model or artificial intelligence network model parameter based on the first positioning request information is supported;   whether multiple artificial intelligence network models or multiple sets of artificial intelligence network model parameters are supported; or   whether obtaining or optimizing positioning signal measurement information and/or location information through an artificial intelligence network model or artificial intelligence network model parameter is supported.   
     
     
         13 . A positioning method, comprising:
 sending, by a second communication device, first positioning request information; and   receiving, by the second communication device, a target artificial intelligence network model and/or target artificial intelligence network model parameter, wherein the target artificial intelligence network model is used for obtaining or optimizing positioning signal measurement information of a target terminal and/or location information of a target terminal.   
     
     
         14 . The positioning method according to  claim 13 , wherein the first positioning request information comprises at least one of the following:
 first measurement information;   ID of artificial intelligence network model and/or artificial intelligence network model parameter;   artificial intelligence network model;   some or all of artificial intelligence network model parameters;   complexity information of artificial intelligence network model;   type information of artificial intelligence network model;   first parameter information, wherein the first parameter information is used for determining input information and/or output information of artificial intelligence network model, used for determining network structure and/or parameter information of artificial intelligence network model, or used for determining positioning information reported or fed back; or   first indication information, used to indicate whether to request an artificial intelligence network model and/or artificial intelligence network model parameter.   
     
     
         15 . The positioning method according to  claim 14 , wherein the first measurement information comprises at least one of the following:
 positioning signal measurement information of the target terminal;   location information of the target terminal; or   error information, wherein the error information comprises at least one of the following: location error value, measurement error value, and artificial intelligence network model error value or parameter error value.   
     
     
         16 . The positioning method according to  claim 14 , wherein the artificial intelligence network model parameter comprises at least one of the following:
 structure of artificial intelligence network model;   multiplicative coefficient, additive coefficient and/or activation function of each neuron of artificial intelligence network model;   complexity information of artificial intelligence network model;   expected training count of artificial intelligence network model;   application document of artificial intelligence network model;   input format of artificial intelligence network model; or   output format of artificial intelligence network model.   
     
     
         17 . The positioning method according to  claim 14 , wherein the type information of artificial intelligence network model comprises at least one of the following:
 fully connected model;   first type, wherein the first type is terminal location information obtained by a first communication device based on the artificial intelligence network model;   second type, wherein the second type is terminal positioning signal measurement information obtained by the first communication device based on the artificial intelligence network model;   third type, wherein the third type is terminal positioning signal measurement information obtained by the first communication device under assistance of the second communication device based on the artificial intelligence network model;   fourth type, wherein the fourth type is terminal location information obtained by the first communication device under assistance of the second communication device based on the artificial intelligence network model;   fifth type, wherein the fifth type is terminal location information obtained by the second communication device under instruction of the first communication device based on the artificial intelligence network model;   sixth type, wherein the sixth type is terminal positioning signal measurement information obtained by the second communication device under instruction of the first communication device based on the artificial intelligence network model;   seventh type, wherein the seventh type is one of terminal positioning signal measurement information and terminal location information obtained by the first communication device based on the artificial intelligence network model, or the other of the terminal positioning signal measurement information or terminal location information obtained by the second communication device based on the artificial intelligence network model; or   unsupervised model or supervised model.   
     
     
         18 . The positioning method according to  claim 14 , wherein the first parameter information comprises at least one of the following:
 length of CIR;   number of paths in multipath;   bandwidth of CIR;   frequency domain information of signal;   time information;   phase information;   angle information;   energy information;   CIR information processed based on third artificial intelligence model or third artificial intelligence model parameter; or   multipath information processed based on third artificial intelligence model or third artificial intelligence model parameter.   
     
     
         19 . The positioning method according to  claim 14 , further comprising:
 receiving, by the second communication device, second parameter information, wherein the second parameter information comprises at least one of the following:   CIR;   multipath measurement result of first positioning reference signal;   time information;   phase information;   angle information;   energy information;   second indication information, wherein the second indication information is used to indicate whether to obtain or optimize other second parameter information through a fourth artificial intelligence network model structure or fourth artificial intelligence network model parameter, or whether to obtain or optimize the positioning signal measurement information of the target terminal and/or location information of the target terminal through the target artificial intelligence network model;   fourth artificial intelligence network model structure; or   fourth artificial intelligence network model parameter; and   wherein the second parameter information is determined based on the first parameter information.   
     
     
         20 . A communication device, comprising a processor and a memory, wherein the memory stores a program or instructions capable of running on the processor, the program or the instructions, when executed by the processor, causes the processor to implement:
 receiving first positioning request information; and   determining and/or sending a target artificial intelligence network model and/or target artificial intelligence network model parameter in response to the first positioning request information, wherein the target artificial intelligence network model is used for obtaining or optimizing positioning signal measurement information of a target terminal and/or location information of a target terminal.